Predicting a user's preference in a short anonymous interaction session instead of long-term
history is a challenging problem in the real-life session-based recommendation, eg, e …

Predicting the next interaction of a short-term interaction session is a challenging task in
session-based recommendation. Almost all existing works rely on item transition patterns …

Session-based recommendation nowadays plays a vital role in many websites, which aims
to predict users' actions based on anonymous sessions. There have emerged many studies …

Session-based recommendation tries to make use of anonymous session data to deliver
high-quality recommendations under the condition that user profiles and the complete …

Session-based recommendation aims to predict next item based on users' anonymous
behavior sequence within a short time. Recent studies focus on modeling sequential …

Session-based recommendation aims to predict a user's next action based on previous
actions in the current session. The major challenge is to capture authentic and complete …

The problem of session-aware recommendation aims to predict users' next click based on
their current session and historical sessions. Existing session-aware recommendation …

Session-based recommendation is a challenging task. Without access to a user's historical
user-item interactions, the information available in an ongoing session may be very limited …

Session-based recommendation (SBR) is a challenging task, which aims at recommending
items based on anonymous behavior sequences. Almost all the existing solutions for SBR …

Session-based recommendation (SBR) aims to predict a user's next clicked item based on
an anonymous yet short interaction sequence. Previous SBR models, which rely only on the …